CCMetagen: Comprehensive and accurate identification of eukaryotes and prokaryotes in metagenomic data

Vanessa R. Marcelino, Philip T.L.C. Clausen, Jan P. Buchmann, Michelle Wille, Jonathan R. Iredell, Wieland Meyer, Ole Lund, Tania C. Sorrell, Edward C. Holmes

Research output: Contribution to journalArticleResearchpeer-review

12 Citations (Scopus)

Abstract

There is an increasing demand for accurate and fast metagenome classifiers that can not only identify bacteria, but all members of a microbial community. We used a recently developed concept in read mapping to develop a highly accurate metagenomic classification pipeline named CCMetagen. The pipeline substantially outperforms other commonly used software in identifying bacteria and fungi and can efficiently use the entire NCBI nucleotide collection as a reference to detect species with incomplete genome data from all biological kingdoms. CCMetagen is user-friendly, and the results can be easily integrated into microbial community analysis software for streamlined and automated microbiome studies.

Original languageEnglish
Article number103
Number of pages15
JournalGenome Biology
Volume21
Issue number1
DOIs
Publication statusPublished - 28 Apr 2020
Externally publishedYes

Keywords

  • ConClave sorting
  • Fungi
  • Metagenomic classifier
  • Microbiome

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